Department of Mechanical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA.
Department of Mechanical Engineering, University of South Carolina, Columbia, SC 29208, USA.
Sensors (Basel). 2021 Jun 20;21(12):4221. doi: 10.3390/s21124221.
Acoustic waves are widely used in structural health monitoring (SHM) for detecting fatigue cracking. The strain energy released when a fatigue crack advances has the effect of exciting acoustic waves, which travel through the structures and are picked up by the sensors. Piezoelectric wafer active sensors (PWAS) can effectively sense acoustic waves due to fatigue-crack growth. Conventional acoustic-wave passive SHM, which relies on counting the number of acoustic events, cannot precisely estimate the crack length. In the present research, a novel method for estimating the crack length was proposed based on the high-frequency resonances excited in the crack by the energy released when a crack advances. In this method, a PWAS sensor was used to sense the acoustic wave signal and predict the length of the crack that generated the acoustic event. First, FEM analysis was undertaken of acoustic waves generated due to a fatigue-crack growth event on an aluminum-2024 plate. The FEM analysis was used to predict the wave propagation pattern and the acoustic signal received by the PWAS mounted at a distance of 25 mm from the crack. The analysis was carried out for crack lengths of 4 and 8 mm. The presence of the crack produced scattering of the waves generated at the crack tip; this phenomenon was observable in the wave propagation pattern and in the acoustic signals recorded at the PWAS. A study of the signal frequency spectrum revealed peaks and valleys in the spectrum that changed in frequency and amplitude as the crack length was changed from 4 to 8 mm. The number of peaks and valleys was observed to increase as the crack length increased. We suggest this peak-valley pattern in the signal frequency spectrum can be used to determine the crack length from the acoustic signal alone. An experimental investigation was performed to record the acoustic signals in crack lengths of 4 and 8 mm, and the results were found to match well with the FEM predictions.
声波在结构健康监测 (SHM) 中被广泛用于检测疲劳裂纹。当疲劳裂纹扩展时释放的应变能具有激发声波的效果，这些声波在结构中传播并被传感器拾取。压电片主动传感器 (PWAS) 可以有效地感测由于疲劳裂纹扩展而产生的声波。传统的基于声发射计数的被动式声波 SHM 无法精确估计裂纹长度。在本研究中，提出了一种基于裂纹扩展时释放的能量在裂纹中激发高频共振来估计裂纹长度的新方法。在该方法中，使用 PWAS 传感器感测声波信号并预测产生声发射事件的裂纹长度。首先，对铝合金 2024 板上由于疲劳裂纹扩展事件产生的声波进行了有限元分析。有限元分析用于预测 PWAS 传感器在距离裂纹 25mm 处接收的波传播模式和声信号。分析针对 4mm 和 8mm 的裂纹长度进行。裂纹的存在导致在裂纹尖端产生的波散射；这种现象在波传播模式和在 PWAS 上记录的声信号中是可见的。对信号频谱的研究表明，在频谱中存在频率和幅度随裂纹长度从 4mm 变为 8mm 而变化的峰谷。随着裂纹长度的增加，观察到峰谷的数量增加。我们建议，仅从声信号就可以使用信号频谱中的这种峰谷模式来确定裂纹长度。进行了实验研究以记录 4mm 和 8mm 裂纹长度的声信号，结果与有限元预测吻合良好。
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